提交 2eb33d0e 编写于 作者: L liuruilong

add log

上级 0d7f152e
......@@ -80,7 +80,7 @@ kernel void genet_preprocess(texture2d<float, access::read> inTexture [[texture(
gid.y >= outTexture.get_height()) {
return;
}
const auto means = float4(123.68f, 116.78f, 103.94f, 0.0f);
const auto means = float4(128.0f, 128.0f, 128.0f, 0.0f);
const float4 inColor = (inTexture.read(gid) * 255.0 - means) * 0.017;
outTexture.write(float4(inColor.z, inColor.y, inColor.x, 0.0f), gid);
}
......
......@@ -79,7 +79,7 @@ class ViewController: UIViewController {
return
}
do {
let max = 50
let max = 1
let startDate = Date.init()
for i in 0..<max {
try net.predict(inTexture: inTexture) { [weak self] (result) in
......
......@@ -38,7 +38,6 @@
FC0E2DC020EE461F009C1FAC /* ElementwiseAddKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC0E2DBF20EE461F009C1FAC /* ElementwiseAddKernel.swift */; };
FC1B16B320EC9A4F00678B91 /* Kernels.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC1B16B220EC9A4F00678B91 /* Kernels.metal */; };
FC1B186620ECF1C600678B91 /* ResizeKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC1B186520ECF1C600678B91 /* ResizeKernel.swift */; };
FC27990E21341016000B6BAD /* BoxCoder.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC27990D21341016000B6BAD /* BoxCoder.metal */; };
FC3602CC2108819F00FACB58 /* PaddleMobileUnitTest.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC3602CB2108819F00FACB58 /* PaddleMobileUnitTest.swift */; };
FC4CB74920F0B954007C0C6D /* ConvKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FC4CB74820F0B954007C0C6D /* ConvKernel.metal */; };
FC4CB74B20F12C30007C0C6D /* ProgramOptimize.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC4CB74A20F12C30007C0C6D /* ProgramOptimize.swift */; };
......@@ -51,6 +50,7 @@
FC9D038420E23B01000F735A /* Texture.swift in Sources */ = {isa = PBXBuildFile; fileRef = FC9D038320E23B01000F735A /* Texture.swift */; };
FCA3A1632132A4AC00084FE5 /* ReshapeKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */; };
FCA3A1652132A5EB00084FE5 /* Common.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCA3A1642132A5EB00084FE5 /* Common.metal */; };
FCA67B1721364EF000BD58AA /* ConvTransposeKernel.metal in Sources */ = {isa = PBXBuildFile; fileRef = FCA67B1621364EF000BD58AA /* ConvTransposeKernel.metal */; };
FCBCCC572122F41300D94F7E /* DwConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */; };
FCBCCC592122F42700D94F7E /* ConvBNReluOp.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */; };
FCBCCC5B2122F66F00D94F7E /* ConvBNReluKernel.swift in Sources */ = {isa = PBXBuildFile; fileRef = FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */; };
......@@ -136,6 +136,7 @@
FC9D038320E23B01000F735A /* Texture.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = Texture.swift; sourceTree = "<group>"; };
FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = ReshapeKernel.metal; sourceTree = "<group>"; };
FCA3A1642132A5EB00084FE5 /* Common.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = Common.metal; sourceTree = "<group>"; };
FCA67B1621364EF000BD58AA /* ConvTransposeKernel.metal */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.metal; path = ConvTransposeKernel.metal; sourceTree = "<group>"; };
FCBCCC562122F41300D94F7E /* DwConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = DwConvBNReluOp.swift; sourceTree = "<group>"; };
FCBCCC582122F42700D94F7E /* ConvBNReluOp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluOp.swift; sourceTree = "<group>"; };
FCBCCC5A2122F66F00D94F7E /* ConvBNReluKernel.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ConvBNReluKernel.swift; sourceTree = "<group>"; };
......@@ -364,6 +365,7 @@
FCDDC6CE212FE14700E5EF74 /* PriorBoxKernel.metal */,
FCA3A1622132A4AC00084FE5 /* ReshapeKernel.metal */,
FCA3A1642132A5EB00084FE5 /* Common.metal */,
FCA67B1621364EF000BD58AA /* ConvTransposeKernel.metal */,
);
path = metal;
sourceTree = "<group>";
......@@ -529,6 +531,7 @@
FCBCCC612122FBDF00D94F7E /* PriorBoxKernel.swift in Sources */,
FCBCCC5F2122FB3B00D94F7E /* PriorBoxOp.swift in Sources */,
FC9D038220E2312E000F735A /* FetchOp.swift in Sources */,
FCA67B1721364EF000BD58AA /* ConvTransposeKernel.metal in Sources */,
FC039BBD20E11CC20081E9F8 /* Program.swift in Sources */,
FC039BA220E11CB70081E9F8 /* Loader.swift in Sources */,
FCBCCC67212306B000D94F7E /* ConcatOp.swift in Sources */,
......
......@@ -62,7 +62,7 @@ public class Executor<P: PrecisionType> {
queue = inQueue
for block in inProgram.programDesc.blocks {
//block.ops.count
for i in 0..<block.ops.count {
for i in 0..<4 {
let op = block.ops[i]
do {
let op = try OpCreator<P>.shared.creat(device: inDevice, opDesc: op, scope: inProgram.scope)
......@@ -110,13 +110,12 @@ public class Executor<P: PrecisionType> {
}
buffer.addCompletedHandler { (commandbuffer) in
// return;
// let inputArr = resInput.floatArray(res: { (p:P) -> P in
// return p
// })
// writeToLibrary(fileName: "input_hand", array: inputArr)
//
// writeToLibrary(fileName: "genet_input_hand", array: inputArr)
// print("write to library done")
// return
// print(inputArr)
......@@ -125,10 +124,13 @@ public class Executor<P: PrecisionType> {
// print(stridableInput)
// let _: Flo? = input.logDesc(header: "input: ", stridable: true)
// for op in self.ops {
// op.delogOutput()
// }
// return
for i in 0..<self.ops.count {
let op = self.ops[i]
print(" 第 \(i) 个 op: ")
op.delogOutput()
}
return
let afterDate = Date.init()
......
......@@ -97,6 +97,7 @@ class ConvAddOp<P: PrecisionType>: Operator<ConvAddKernel<P>, ConvAddParam<P>>,
}
func delogOutput() {
print(" \(type) output: ")
print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
}
}
......@@ -356,78 +356,6 @@ kernel void depthwise_conv_add_batch_norm_relu_3x3(texture2d_array<float, access
outTexture.write(output, gid.xy, gid.z);
}
struct MetalConvTransposeParam{
ushort kernelW;
ushort kernelH;
ushort strideX;
ushort strideY;
ushort paddingX;
ushort paddingY;
ushort dilationX;
ushort dilationY;
};
kernel void conv_transpose(texture2d_array<float, access::sample> inTexture [[texture(0)]],
texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvTransposeParam &param [[buffer(0)]],
const device float4 *weights [[buffer(1)]],
uint3 gid [[thread_position_in_grid]]){
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) {
return;
}
int input_array_size = inTexture.get_array_size();
uint kernel_one_output_slice = input_array_size * param.kernelW * param.kernelH;
uint kernel_stride_z = gid.z * 4 * (kernel_one_output_slice);
constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
float4 output;
for (int w = 0; w < param.kernelW; ++w) {
int input_x = (gid.x - w * param.dilationX + param.paddingX) / param.strideX;
if (input_x < 0 || input_x >= int(inTexture.get_width())) {
continue;
}
for (int h = 0; h < param.kernelH; ++h) {
int input_y = (gid.y - h * param.dilationY + param.paddingY) / param.strideY;
if (input_y < 0 || input_y >= int(inTexture.get_height())) {
continue;
}
uint kernel_index = (w * param.kernelH + h) * inTexture.get_array_size();
for (int slice = 0; slice < input_array_size; ++slice) {
float4 input;
float4 kernel_slice = weights[kernel_stride_z + 0 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice1 = weights[kernel_stride_z + 1 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice2 = weights[kernel_stride_z + 2 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice3 = weights[kernel_stride_z + 3 * kernel_one_output_slice + kernel_index + slice];
input = inTexture.sample(sample, float2(input_x, input_x), slice);
output.x += dot(input, kernel_slice);
output.x += dot(input, kernel_slice1);
output.x += dot(input, kernel_slice2);
output.x += dot(input, kernel_slice3);
}
}
}
outTexture.write(output, gid.xy, gid.z);
}
// conv
#pragma mark -- conv
kernel void conv_3x3(texture2d_array<float, access::sample> inTexture [[texture(0)]],
......
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <metal_stdlib>
using namespace metal;
struct MetalConvTransposeParam{
ushort kernelW;
ushort kernelH;
ushort strideX;
ushort strideY;
ushort paddingX;
ushort paddingY;
ushort dilationX;
ushort dilationY;
};
kernel void conv_transpose(texture2d_array<float, access::sample> inTexture [[texture(0)]],
texture2d_array<float, access::write> outTexture [[texture(1)]],
constant MetalConvTransposeParam &param [[buffer(0)]],
const device float4 *weights [[buffer(1)]],
uint3 gid [[thread_position_in_grid]]){
if (gid.x >= outTexture.get_width() ||
gid.y >= outTexture.get_height() ||
gid.z >= outTexture.get_array_size()) {
return;
}
int input_array_size = inTexture.get_array_size();
uint kernel_one_output_slice = input_array_size * param.kernelW * param.kernelH;
uint kernel_stride_z = gid.z * 4 * (kernel_one_output_slice);
constexpr sampler sample(coord::pixel, filter::nearest, address::clamp_to_zero);
float4 output;
for (int w = 0; w < param.kernelW; ++w) {
int input_x = (gid.x - w * param.dilationX + param.paddingX) / param.strideX;
if (input_x < 0 || input_x >= int(inTexture.get_width())) {
continue;
}
for (int h = 0; h < param.kernelH; ++h) {
int input_y = (gid.y - h * param.dilationY + param.paddingY) / param.strideY;
if (input_y < 0 || input_y >= int(inTexture.get_height())) {
continue;
}
uint kernel_index = (w * param.kernelH + h) * inTexture.get_array_size();
for (int slice = 0; slice < input_array_size; ++slice) {
float4 input;
float4 kernel_slice = weights[kernel_stride_z + 0 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice1 = weights[kernel_stride_z + 1 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice2 = weights[kernel_stride_z + 2 * kernel_one_output_slice + kernel_index + slice];
float4 kernel_slice3 = weights[kernel_stride_z + 3 * kernel_one_output_slice + kernel_index + slice];
input = inTexture.sample(sample, float2(input_x, input_x), slice);
output.x += dot(input, kernel_slice);
output.x += dot(input, kernel_slice1);
output.x += dot(input, kernel_slice2);
output.x += dot(input, kernel_slice3);
}
}
}
outTexture.write(output, gid.xy, gid.z);
}
......@@ -58,12 +58,16 @@ class PoolOp<P: PrecisionType>: Operator<PoolKernel<P>, PoolParam<P>>, Runable,
}
func delogOutput() {
print("pool2d delog")
let _: P? = para.input.metalTexture.logDesc(header: "pool2d input: ", stridable: true)
print(para.ksize)
print(para.stride)
print(para.padding)
print(para.poolType)
let _: P? = para.output.metalTexture.logDesc(header: "pool2d output: ", stridable: true)
print(" \(type) output: ")
print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
// print("pool2d delog")
// let _: P? = para.input.metalTexture.logDesc(header: "pool2d input: ", stridable: true)
// print(para.ksize)
// print(para.stride)
// print(para.padding)
// print(para.poolType)
// let _: P? = para.output.metalTexture.logDesc(header: "pool2d output: ", stridable: true)
}
}
......@@ -50,8 +50,8 @@ class PreluOp<P: PrecisionType>: Operator<PreluKernel<P>, PreluParam<P>>, Runabl
}
func delogOutput() {
print("softmax delog")
let _: P? = para.input.metalTexture.logDesc(header: "softmax input: ", stridable: false)
let _: P? = para.output.metalTexture.logDesc(header: "softmax output: ", stridable: false)
// print("softmax delog")
// let _: P? = para.input.metalTexture.logDesc(header: "softmax input: ", stridable: false)
// let _: P? = para.output.metalTexture.logDesc(header: "softmax output: ", stridable: false)
}
}
......@@ -43,6 +43,12 @@ class ReluOp<P: PrecisionType>: Operator<ReluKernel<P>, ReluParam<P>>, Runable,
throw error
}
}
func delogOutput() {
print(" \(type) output: ")
print(para.output.metalTexture.toTensor(dim: (n: para.output.tensorDim[0], c: para.output.tensorDim[1], h: para.output.tensorDim[2], w: para.output.tensorDim[3])).strideArray())
}
}
......
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